About the Course
Over eight weeks, our Data Engineering course will provide you with a technical overview of how to understand, leverage, and report data. You will be taught how to source, prepare, and manage historical data. You will also learn about the history and principles of database systems, how to clean raw data, and how to use SQL to load and query data in databases.
You Will Learn To:
- Understand databases, data classification, data formats, and data profiles.
- Apply data privacy and security, data ingestion, data quality and preparation techniques.
- Identify the principles and best practices of relational databases.
- Identify the principles and best practices of relational databases.
- Design a system, known as data warehousing, used for reporting and data analysis.
Methodologies and Techniques:
You Will Be Able To:
- Build and extract insights from document databases.
- Create reports and dashboards in Tableau using an analytical datastore.
- Develop a coherent, concise, and realistic analysis, and apply your knowledge and understanding of creating an automated end-to-end data pipeline.
- Evaluate the similarities and differences between joins and subqueries in coding and decide which is more suitable based on your use case.
- Implement data collection techniques, such as web scraping and survey.
- Populate a graph database and extract insights from graph datasets.
Request for Information
Career Outlook
$
112
k
The average salary for a data engineer in the US
#
1
The rank of data engineer among the fastest-growing jobs in tech
50
%
The year-over-year growth in the number of open data engineering positions
Potential Data Engineering Job Titles
- Big Data Engineer
- Business Intelligence Engineer
- Computer Vision Engineer
- Data Architect
- Machine Learning Engineer
Meet Your Instructors
Shree Bharadwaj, MScData Engineering and Strategic Data Storytelling Read More
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Shree Bharadwaj works at West Monroe, a management consulting company. As a M&A Data and AI Practice Lead, he advises private equity and venture capital firms and C-level executives on value creation, post-close synergies, and data and analytics (BI/AI) strategies focused on business outcomes. In his previous executive leadership role at Syndigo, he led the data strategy, data science, next-gen platform and M&A integrations. His expertise revolves around driving innovation, standardization, development and operationalization of machine learning models, data engineering at scale using on-premise and cloud platforms, effective data visualizations, model-driven design, and algorithmic thinking. Bharadwaj was elected to the Global Standards Architecture Board at GS1, where he worked with global industry leaders to develop standards, road maps, and governance and compliance requirements relating to food services, healthcare, retail, supply chain, and CPG/FMCG verticals. His experience spans across multiple industries that include AdTech, EdTech, Fintech, healthcare, MarTech, public safety, retail, and telecom in organizations that range from startups to Fortune 100 companies.
Ashish Pujari, MScData Engineering Read More
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Ashish Pujari is a leader in data and analytics, IT strategy, and technology consulting. As a Director of Analytics at GLG, Pujari leads the design and implementation of business intelligence, predictive analytics, and visualization. Before joining GLG, Pujari served as an AVP of Analytics Architecture for CNA Insurance, where he was responsible for insurance analytics platforms and data strategy. Pujari specializes in big-data analytics, cloud computing, algorithm development, application and database design, decision management, and visualization technologies. He has been involved in technology consulting in finance, banking, insurance, and communications domains for clients in Europe, North America, and Asia.
Do you have questions?
The University of Chicago Approach to Online Learning
Our online learning programs are crafted with your specific needs in mind. Programs combine e-learning with live, interactive sessions to strengthen your skill set while maximizing your time. We couple academic theory and business knowledge with practical, real-world application. Through online learning sessions, you will have an opportunity to grow your professional network and interact with University of Chicago instructors and your classmates.
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What Our Participants Say
This is an essential program, mandatory for all those who want to understand more about artificial intelligence and data science. It is the gateway to an urgent and continuous future.
This program increased my confidence level around AI and ML knowledge and prepared me for the next level in my career in the AI ecosystem. I am now able to approach any AI project while keeping ethical value as an important consideration in mind when building algorithms.
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